Summary information

Study title

TeleScope: A Longitudinal Dataset for Aggregated User Interactions and Information Dissemination on Telegram

Creator

Gangopadhyay, Susmita ( GESIS – Leibniz Institute for the Social Sciences)
Dessi, Danilo ( University of Sharjah)
Dimitrov, Dimitar ( GESIS – Leibniz Institute for the Social Sciences)
Dietze, Stefan ( Heinrich Heine University Düsseldorf)

Study number / PID

10.7802/2825 (GESIS)

10.7802/2825 (DOI)

Data access

Information not available

Series

Not available

Abstract

TeleScope is an extensive dataset suite that comprises metadata for about 500K Telegram channels and downloaded message metadata from all 71K public channels within this 500k channels accounting for about 120M crawled messages. In addition to metadata, TeleScope suite provides enrichments like language detection and active periods for each channel and telegram entity extracted from messages. It also comprises channel connections and user interaction data built using Telegram’s message-forwarding feature to study multiple use cases including information spread and message-forwarding patterns. The dataset is designed for diverse applications, independent of specific research objectives, and sufficiently versatile to facilitate the replication of social media studies comparable to those conducted on platforms like X (former Twitter). Further information on the content of the files can be found in the file TeleScope_readme_v1-0-0.txt (see 'Technical Report'). keywords: Computational Social Science; Information Science, Web and Social Media; text analysis; text processing; text communication; social media; Online discourse; Information Dissemination; Information Analysis

Topics

Not available

Methodology

Data collection period

01/02/2024 - 01/10/2024

Country

Time dimension

Longitudinal (panel study)

Analysis unit

Not available

Universe

Initial selection is based on top 100 TGStat channels according to Subscribers, Reach and Citation Criteria. The growth of the dataset is based on snowball sampling.

Sampling procedure

The growth of the dataset is based on snowball sampling

Kind of data

Not available

Data collection mode

Web Crawling; Web Scraping

Access

Publisher

GESIS Data Archive for the Social Sciences

Publication year

2025

Terms of data access

Free access (without registration) - The research data can be downloaded directly by anyone without further limitations.

Related publications

Not available